fix: relative to absolute imports

BoevaLab · Oct 26, 2023 · f98957c · f98957c
1 parent 72f2674
commit f98957c
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Showing 5 changed files with 10 additions and 10 deletions.
diff --git a/sparsesurv/tests/test_aft.py b/sparsesurv/tests/test_aft.py
@@ -3,10 +3,10 @@
 import numpy as np
 import pytest
 import torch
-from .get_data_arrays import get_1d_array
+from sparsesurv.tests.get_data_arrays import get_1d_array
 
 from sparsesurv.loss import aft_negative_likelihood
-from sparsesurv.utils import normal_density
+from sparsesurv.tests.test_utils import normal_density
 
 
 def aft_calculation(linear_predictor, time, event):

diff --git a/sparsesurv/tests/test_breslow.py b/sparsesurv/tests/test_breslow.py
@@ -3,7 +3,7 @@
 import numpy as np
 
 import pytest
-from .get_data_arrays import get_1d_array
+from sparsesurv.tests.get_data_arrays import get_1d_array
 
 from sparsesurv.loss import breslow_negative_likelihood
 

diff --git a/sparsesurv/tests/test_eh.py b/sparsesurv/tests/test_eh.py
@@ -4,9 +4,9 @@
 import pytest
 import torch
 
-from ..loss import eh_negative_likelihood
-from .get_data_arrays import get_2d_array
-from .test_utils import normal_density
+from sparsesurv.loss import eh_negative_likelihood
+from sparsesurv.tests.get_data_arrays import get_2d_array
+from sparsesurv.tests.test_utils import normal_density
 
 
 def eh_calculation(linear_predictor, time, event):

diff --git a/sparsesurv/tests/test_eh_gradient.py b/sparsesurv/tests/test_eh_gradient.py
@@ -1,11 +1,11 @@
 import numpy as np
-import pandas as pd
+
 import torch
-from .get_data_arrays import get_2d_array
+from sparsesurv.tests.get_data_arrays import get_2d_array
 
 from sparsesurv.gradients import eh_gradient
 
-from .test_eh import eh_calculation
+from sparsesurv.tests.test_eh import eh_calculation
 
 
 def get_eh_gradient(case="default"):

diff --git a/sparsesurv/tests/test_utils.py b/sparsesurv/tests/test_utils.py
@@ -1,6 +1,6 @@
 import torch
 
-from ..constants import PDF_PREFACTOR
+from sparsesurv.constants import PDF_PREFACTOR
 
 
 def normal_density(x: torch.Tensor) -> torch.Tensor: